NMR spectroscopy on biological macromolecules generates vast amounts of data and requires intricate knowledge of the molecular system under study for successful analysis of the acquired data. The size and complexity of the molecular systems have grown to the point where software integration is essential to improve the productivity of NMR studies, maximize the efficiency of NMR data analyses, and guarantee the validity of such analyses. In addition, there exist a large number of valuable NMR analysis tools, intricately interdependent in the information they provide and require. Due to this interdependence, a conceptual data model for both raw and analyzed NMR data is required to provide a database and software integration system capable of format conversion amongst the codependent software. In the absence of such a software integration system, much NMR data is considered too complicated to be thoroughly treated and is effectively discarded. Until such a system is developed and distributed, the bulk of the information provided by biological NMR spectroscopy will continue to be lost. The long term goal of this ongoing research project is to make biomolecular NMR analysis faster, easier, more precise, and less expensive by developing and distributing such an integrated software environment, termed CONNJUR. Utilizing a standard three-tier architecture, CONNJUR provides a customizable user interface front-end, a middle tier which wraps third-party NMR software tools, and a relational database back-end for storage of all data and metadata pertaining to a given experimental processing pipeline. The CONNJUR database is implemented from a relational data model of biomolecular NMR spectroscopy, capturing the attributes of raw and derived data, as well as the syntax and semantics of the various data processing steps. Most importantly, the data model stores the interrelationships between the various pieces of data, such that the user can easily keep track of the provenance and lineage of all data elements within the workflow, thus completely documenting all necessary aspects of an experiment.

Public Health Relevance

Biomolecular NMR (Nuclear Magnetic Resonance) is a critically important technique used daily by thousands of researchers for drug discovery and design as well as for the analysis of the biochemical basis of disease. Despite enormous advances in the acquisition hardware, this valuable NMR data is currently processed and analyzed using dozens of independent software tools which are incapable of either sharing data components between each other or of being managed using a single software environment. CONNJUR aims to solve this problem by providing a software integration environment which will increase the speed, volume and accuracy of data analysis and thereby both decrease the cost of NMR research and increase the promise of translating research findings to medical therapies.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM083072-04
Application #
8197499
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Wehrle, Janna P
Project Start
2008-12-01
Project End
2014-11-30
Budget Start
2011-12-01
Budget End
2014-11-30
Support Year
4
Fiscal Year
2012
Total Cost
$295,612
Indirect Cost
$73,627
Name
University of Connecticut
Department
Microbiology/Immun/Virology
Type
Schools of Medicine
DUNS #
022254226
City
Farmington
State
CT
Country
United States
Zip Code
06030
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Ellis, Heidi J C; Nowling, Ronald J; Vyas, Jay et al. (2011) Iterative Development of an Application to Support Nuclear Magnetic Resonance Data Analysis of Proteins. Proc Int Conf Inf Technol New Gener :1014-1020
Nowling, Ronald J; Vyas, Jay; Weatherby, Gerard et al. (2011) CONNJUR spectrum translator: an open source application for reformatting NMR spectral data. J Biomol NMR 50:83-9
Vyas, Jay; Nowling, Ronald J; Meusburger, Thomas et al. (2010) MimoSA: a system for minimotif annotation. BMC Bioinformatics 11:328
Gryk, Michael R; Vyas, Jay; Maciejewski, Mark W (2010) Biomolecular NMR data analysis. Prog Nucl Magn Reson Spectrosc 56:329-45